New Opportunities for Sentiment Analysis and Information Processing

New Opportunities for Sentiment Analysis and Information Processing

Aakanksha Sharaff (National Institute of Technology, Raipur, India), G. R. Sinha (Myanmar Institute of Information Technology, Mandalay, Myanmar), and Surbhi Bhatia (King Faisal University, Saudi Arabia)
Release Date: June, 2021|Copyright: © 2021 |Pages: 311
DOI: 10.4018/978-1-7998-8061-5
ISBN13: 9781799880615|ISBN10: 1799880613|ISBN13 Softcover: 9781799880622|EISBN13: 9781799880639
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Description & Coverage
Description:

Multinational organizations have begun to realize that sentiment mining plays an important role for decision making and market strategy. The revolutionary growth of digital marketing not only changes the market game, but also brings forth new opportunities for skilled professionals and expertise. Currently, the technologies are rapidly changing, and artificial intelligence (AI) and machine learning are contributing as game-changing technologies. These are not only trending but are also increasingly popular among data scientists and data analysts.

New Opportunities for Sentiment Analysis and Information Processing provides interdisciplinary research in information retrieval and sentiment analysis including studies on extracting sentiments from textual data, sentiment visualization-based dimensionality reduction for multiple features, and deep learning-based multi-domain sentiment extraction. The book also optimizes techniques used for sentiment identification and examines applications of sentiment analysis and emotion detection. Covering such topics as communication networks, natural language processing, and semantic analysis, this book is essential for data scientists, data analysts, IT specialists, scientists, researchers, academicians, and students.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • Communication Network
  • Deep Belief Network
  • Emotion Detection
  • Emotional Intelligence
  • Generative Adversarial Network
  • Information Processing
  • Machine Learning
  • Natural Language Processing
  • Opinion Mining
  • Polarity Identification
  • Semantic Analysis
  • Semantic Orientation
  • Sentiment Analysis
  • Sentiment Extraction
  • Social Media
  • Tag Cloud Sentiment Values
  • Text Mining
  • Visualization
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Editor/Author Biographies
Aakanksha Sharaff has completed her graduation in Computer Science and Engineering in 2010 from Government Engineering College, Bilaspur (C.G.). She has completed her post graduation Master of Technology in 2012 in Computer Science & Engineering (Specialization- Software Engineering) from National Institute of Technology, Rourkela and completed Ph.D. degree in Computer Science & Engineering in 2017 from National Institute of Technology Raipur, India. Her area of interest is Software Engineering, Data Mining, Text Mining and Information Retrieval. She is currently working as an Assistant Professor at NIT Raipur India.
Dr G R Sinha is Adjunct Professor at International Institute of Information Technology (IIIT) Bangalore and currently deputed as Professor at Myanmar Institute of Information Technology (MIIT) Mandalay Myanmar. He obtained his B.E. (Electronics Engineering) and M.Tech. (Computer Technology) with Gold Medal from National Institute of Technology Raipur. He received his Ph.D. in Electronics

Surbhi Bhatia, PMP®, completed her doctorate from Banasthali Vidyapith, India and is currently working in the College of Computer Sciences and Information Technology, King Faisal University, Saudi Arabia. With over 8 years of academic experience, she has authored 41 papers in conferences, edited books and reputed SCI journals with impact factor and has 9 patents, published and granted from USA, Australia, and India in her list. She has authored 2 books and edited 7 books from Springer, Elsevier, and Wiley. She has been awarded 2 funded research project grants from the Deanship of Scientific Research at King Faisal University and from the Ministry of Education, Saudi Arabia. Her research interests include machine learning, sentiment analysis, and information retrieval.

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